analyze-project

analyze-project is a skill for Claude Code, Codex from Ghosteken/agent-harness. It costs 39 tokens per session (3,029 once invoked), scanned A, a copy of analyze-project, MIT.

A postmortem tool for AI-assisted coding sessions that examines what changed, where rework occurred, and what caused the problems. It uses session records to separate issues in the request, agent, codebase, testing, or task complexity.

In plain words
What is it for?
Use it to review scope drift, repeated rework, weak opening prompts, and codebase areas that repeatedly cause trouble, then produce evidence-based recommendations.
Why use it?
It helps explain why a coding session went off track instead of only listing the final changes. This makes it easier to improve prompts, repository health, and validation steps.

Skill for Claude CodeCodex

Part of the agent-harness plugin — 173 skills, 11 commands, 12 agents shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/ghosteken/agent-harness/analyze-project
Any agent
npx skills add Ghosteken/agent-harness --skill analyze-project
Clone the repo
git clone --depth 1 https://github.com/Ghosteken/agent-harness

Made for: Claude Code, Codex.

Or install agent-harness, the plugin that ships this one along with the rest of its 173 skills, 11 commands, 12 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for analyze-project

README.md
[![agentmods](https://agentmods.dev/badge/skills/ghosteken/agent-harness/analyze-project.svg)](https://agentmods.dev/skills/ghosteken/agent-harness/analyze-project)
Your own site
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/analyze-project"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/analyze-project.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,029 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.03029
Opus 5 $0.00019 $0.01515
Sonnet 5 $0.00008 $0.00606
Haiku 4.5 $0.00004 $0.00303

Measured yesterday against content hash 02324733ed1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyze-project scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

86% identical to analyze-project — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

archive/skills-community/analyze-project/SKILL.md · 445 lines

How it starts

The opening of the file, as written. The whole thing — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/analyze-project — Root Cause Analyst Workflow

Analyze AI-assisted coding sessions in ~/.gemini/antigravity/brain/ and produce a report that explains not just what happened, but why it happened, who/what caused it, and what should change next time.

Goal

For each session, determine:

  1. What changed from the initial ask to the final executed work
  2. Whether the main cause was:
    • user/spec
    • agent
    • repo/codebase
    • validation/testing
    • legitimate task complexity
  3. Whether the opening prompt was sufficient
  4. Which files/subsystems repeatedly correlate with struggle
  5. What changes would most improve future sessions

When to Use

  • You need a postmortem on AI-assisted coding sessions, especially when scope drift or repeated rework occurred.
  • You want root-cause analysis that separates user/spec issues from agent mistakes, repo friction, or validation gaps.
  • You need evidence-backed recommendations for improving future prompts, repo health, or delivery workflows.

Global Rules

  • Treat .resolved.N counts as iteration signals, not proof of failure
  • Separate human-added scope, necessary discovered scope, and agent-introduced scope
  • Separate agent error from repo friction
  • Every diagnosis must include evidence and confidence
  • Confidence levels:
    • High = direct artifact/timestamp evidence
    • Medium = multiple supporting signals
    • Low = plausible inference, not directly proven
  • Evidence precedence:
    • artifact contents > timestamps > metadata summaries > inference
  • If evidence is weak, say so

Step 0.5: Session Intent Classification

Classify the primary session intent from objective + artifacts:

  • DELIVERY
  • DEBUGGING
  • REFACTOR
  • RESEARCH
  • EXPLORATION
  • AUDIT_ANALYSIS

Record:

  • session_intent
  • session_intent_confidence

Use intent to contextualize severity and rework shape. Do not judge exploratory or research sessions by the same standards as narrow delivery sessions.

Read the full file on GitHub · 445 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 445 lines · 39 tokens per session scan A 02324733ed1b

Subscribe to this mod's changes

analyze-project is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 3,029 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to analyze-project, differing in 10 lines, and is treated as a copy.